Colon and lung cancer classification from multi-modal images using resilient and efficient neural network architectures-Reference-Cited by-同舟云学术

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Colon and lung cancer classification from multi-modal images using resilient and efficient neural network architectures

Published:2024-05 Issue:9 Volume:10 Page:e30625
ISSN:2405-8440
Container-title:Heliyon
language:en
Short-container-title:Heliyon

Author:

Uddin A. Hasib,Chen Yen-Lin^ORCID,Akter Miss Rokeya,Ku Chin Soon,Yang Jing,Por Lip Yee

Publisher

Elsevier BV

Reference57 articles.

1. Histopathology images predict multi-omics aberrations and prognoses in colorectal cancer patients;Tsai;Nat. Commun.,2023

2. Pathological image classification via embedded fusion mutual learning;Li;Biomed. Signal Process Control,2023

3. Multi-channel auto-encoders for learning domain invariant representations enabling superior classification of histopathology images;Moyes;Med. Image Anal.,2023

4. Lung and colon cancer classification using hybrid principle component analysis network‐extreme learning machine;Naga Raju;Concurr. Comput.,2023

5. CJT-DEO: Condorcet's Jury Theorem and Differential Evolution Optimization based ensemble of deep neural networks for pulmonary and Colorectal cancer classification;Srivastava;Appl. Soft Comput.,2023

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Holistic Approach to Implementing Artificial Intelligence in Lung Cancer;Indian Journal of Surgical Oncology;2024-09-05

2. A Review on Lung and Colon Combine Cancer Detection using ML and DL Techniques;International Journal of Scientific Research in Computer Science, Engineering and Information Technology;2024-09-05

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